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<div class="title">ia_fpcs.hpp</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *  Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *  Copyright (c) 2014-, Open Perception, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *  Copyright (C) 2008 Ben Gurion University of the Negev, Beer Sheva, Israel.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *  All rights reserved</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *  Redistribution and use in source and binary forms, with or without</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *  modification, are permitted provided that the following conditions are met</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *   * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *     notice, this list of conditions and the following disclaimer.</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *   * Redistributions in binary form must reproduce the above</span></div>
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<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160; </div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="preprocessor">#ifndef PCL_REGISTRATION_IMPL_IA_FPCS_H_</span></div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="preprocessor">#define PCL_REGISTRATION_IMPL_IA_FPCS_H_</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160; </div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#include &lt;pcl/registration/ia_fpcs.h&gt;</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="common_2time_8h.html">pcl/common/time.h</a>&gt;</span></div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="common_2include_2pcl_2common_2distances_8h.html">pcl/common/distances.h</a>&gt;</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#include &lt;pcl/sample_consensus/sac_model_plane.h&gt;</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="preprocessor">#include &lt;pcl/registration/transformation_estimation_3point.h&gt;</span></div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160; </div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keyword">inline</span> <span class="keywordtype">float</span></div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;pcl::getMeanPointDensity (<span class="keyword">const</span> <span class="keyword">typename</span> pcl::PointCloud&lt;PointT&gt;::ConstPtr &amp;cloud, <span class="keywordtype">float</span> max_dist, <span class="keywordtype">int</span> nr_threads)</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;{</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span> max_dist_sqr = max_dist * max_dist;</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  <span class="keyword">const</span> std::size_t s = cloud.size ();</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160; </div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;  <a class="code" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree &lt;PointT&gt;</a> tree;</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;  tree.<a class="code" href="classpcl_1_1search_1_1_kd_tree.html#a457ebf1fc8f25e3b45d0bf9d55880f6f">setInputCloud</a> (cloud);</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160; </div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;  <span class="keywordtype">float</span> mean_dist = 0.f;</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  <span class="keywordtype">int</span> num = 0;</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  std::vector &lt;int&gt; ids (2);</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  std::vector &lt;float&gt; dists_sqr (2);</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160; </div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="preprocessor">#pragma omp parallel for \</span></div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="preprocessor">  reduction (+:mean_dist, num) \</span></div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;<span class="preprocessor">  private (ids, dists_sqr) shared (tree, cloud) \</span></div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;<span class="preprocessor">  default (none)num_threads (nr_threads)</span></div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160; </div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 1000; i++)</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  {</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    tree.<a class="code" href="classpcl_1_1search_1_1_kd_tree.html#a6be8fe286786c3b1aeda7d5369f9cb3e">nearestKSearch</a> (cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[rand () % s], 2, ids, dists_sqr);</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <span class="keywordflow">if</span> (dists_sqr[1] &lt; max_dist_sqr)</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    {</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;      mean_dist += std::sqrt (dists_sqr[1]);</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;      num++;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    }</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  }</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160; </div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="keywordflow">return</span> (mean_dist / num);</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;};</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160; </div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160; </div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keyword">inline</span> <span class="keywordtype">float</span></div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;pcl::getMeanPointDensity (<span class="keyword">const</span> <span class="keyword">typename</span> pcl::PointCloud&lt;PointT&gt;::ConstPtr &amp;cloud, <span class="keyword">const</span> std::vector &lt;int&gt; &amp;indices,</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  <span class="keywordtype">float</span> max_dist, <span class="keywordtype">int</span> nr_threads)</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;{</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span> max_dist_sqr = max_dist * max_dist;</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  <span class="keyword">const</span> std::size_t s = indices.size ();</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160; </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  <a class="code" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree &lt;PointT&gt;</a> tree;</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  tree.<a class="code" href="classpcl_1_1search_1_1_kd_tree.html#a457ebf1fc8f25e3b45d0bf9d55880f6f">setInputCloud</a> (cloud);</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160; </div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;  <span class="keywordtype">float</span> mean_dist = 0.f;</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;  <span class="keywordtype">int</span> num = 0;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;  std::vector &lt;int&gt; ids (2);</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  std::vector &lt;float&gt; dists_sqr (2);</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160; </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;<span class="preprocessor">#pragma omp parallel for \</span></div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;<span class="preprocessor">  reduction (+:mean_dist, num) \</span></div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;<span class="preprocessor">  private (ids, dists_sqr) shared (tree, cloud, indices)    \</span></div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;<span class="preprocessor">  default (none)num_threads (nr_threads)</span></div>
<div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#aa7d70d10a9c44c2f1ffa575c8c657da6">  104</a></span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160; </div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 1000; i++)</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  {</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    tree.<a class="code" href="classpcl_1_1search_1_1_kd_tree.html#a6be8fe286786c3b1aeda7d5369f9cb3e">nearestKSearch</a> (cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[indices[rand () % s]], 2, ids, dists_sqr);</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <span class="keywordflow">if</span> (dists_sqr[1] &lt; max_dist_sqr)</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    {</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;      mean_dist += std::sqrt (dists_sqr[1]);</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      num++;</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    }</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;  }</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;  <span class="keywordflow">return</span> (mean_dist / num);</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;};</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160; </div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160; </div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#aa7d70d10a9c44c2f1ffa575c8c657da6">  122</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::FPCSInitialAlignment</a> () :</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  source_normals_ (),</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;  target_normals_ (),</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;  nr_threads_ (1),</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;  approx_overlap_ (0.5f),</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;  delta_ (1.f),</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;  score_threshold_ (FLT_MAX),</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;  nr_samples_ (0),</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;  max_norm_diff_ (90.f),</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;  max_runtime_ (0),</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;  fitness_score_ (FLT_MAX),</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;  diameter_ (),</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;  max_base_diameter_sqr_ (),</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  use_normals_ (<span class="keyword">false</span>),</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  normalize_delta_ (<span class="keyword">true</span>),</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  max_pair_diff_ (),</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  max_edge_diff_ (),</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  coincidation_limit_ (),</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  max_mse_ (),</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  max_inlier_dist_sqr_ (),</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  small_error_ (0.00001f)</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;{</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;  reg_name_ = <span class="stringliteral">&quot;pcl::registration::FPCSInitialAlignment&quot;</span>;</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;  max_iterations_ = 0;</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;  ransac_iterations_ = 1000;</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;  transformation_estimation_.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1registration_1_1_transformation_estimation3_point.html">pcl::registration::TransformationEstimation3Point &lt;PointSource, PointTarget&gt;</a>);</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;}</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160; </div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160; </div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00153"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ab2c4309ae91b6c3bc6f5480cad22ec67">  153</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::computeTransformation</a> (</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;  PointCloudSource &amp;output,</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;  <span class="keyword">const</span> Eigen::Matrix4f &amp;guess)</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;{</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;  <span class="keywordflow">if</span> (!initCompute ())</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160; </div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  final_transformation_ = guess;</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;  <span class="keywordtype">bool</span> abort = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;  std::vector &lt;MatchingCandidates&gt; all_candidates (max_iterations_);</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;  <a class="code" href="classpcl_1_1_stop_watch.html">pcl::StopWatch</a> timer;</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160; </div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;<span class="preprocessor">  #ifdef _OPENMP</span></div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;<span class="preprocessor">  #pragma omp parallel num_threads (nr_threads_)</span></div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;<span class="preprocessor">  #endif</span></div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;  {</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;<span class="preprocessor">    #ifdef _OPENMP</span></div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    std::srand (<span class="keyword">static_cast &lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span> (std::time (NULL)) ^ omp_get_thread_num ());    </div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;<span class="preprocessor">    #pragma omp for schedule (dynamic)</span></div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;<span class="preprocessor">    #endif</span></div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; max_iterations_; i++)</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    {</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160; </div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;<span class="preprocessor">      #ifdef _OPENMP</span></div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;<span class="preprocessor">      #pragma omp flush (abort)</span></div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;<span class="preprocessor">      #endif</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160; </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;      MatchingCandidates candidates (1);</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;      std::vector &lt;int&gt; base_indices (4);</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;      <span class="keywordtype">float</span> ratio[2];</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;      all_candidates[i] = candidates;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160; </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;      <span class="keywordflow">if</span> (!abort)</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;      {</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        <span class="comment">// select four coplanar point base</span></div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        <span class="keywordflow">if</span> (selectBase (base_indices, ratio) == 0)</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        {</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;          <span class="comment">// calculate candidate pair correspondences using diagonal lenghts of base</span></div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;          pcl::Correspondences pairs_a, pairs_b;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;          <span class="keywordflow">if</span> (bruteForceCorrespondences (base_indices[0], base_indices[1], pairs_a) == 0 &amp;&amp;</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;            bruteForceCorrespondences (base_indices[2], base_indices[3], pairs_b) == 0)</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;          {</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;            <span class="comment">// determine candidate matches by combining pair correspondences based on segment distances</span></div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;            std::vector &lt;std::vector &lt;int&gt; &gt; matches;</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;            <span class="keywordflow">if</span> (determineBaseMatches (base_indices, matches, pairs_a, pairs_b, ratio) == 0)</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;            {</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;              <span class="comment">// check and evaluate candidate matches and store them</span></div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;              handleMatches (base_indices, matches, candidates);</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;              <span class="keywordflow">if</span> (candidates.size () != 0)</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;                all_candidates[i] = candidates;</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;            }</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;          }</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        }</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160; </div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        <span class="comment">// check terminate early (time or fitness_score threshold reached)</span></div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        abort = (candidates.size () &gt; 0 ? candidates[0].fitness_score &lt; score_threshold_ : abort);</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        abort = (abort ? abort : timer.<a class="code" href="classpcl_1_1_stop_watch.html#a13f07f01df8ea1feb8d7d5fe3a0d22eb">getTimeSeconds</a> () &gt; max_runtime_);</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160; </div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160; </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;<span class="preprocessor">        #ifdef _OPENMP</span></div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;<span class="preprocessor">        #pragma omp flush (abort)</span></div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;<span class="preprocessor">        #endif</span></div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;      }</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    }</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;  }</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  </div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160; </div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;  <span class="comment">// determine best match over all trys</span></div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;  finalCompute (all_candidates);</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160; </div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  <span class="comment">// apply the final transformation</span></div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;  <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*input_, output, final_transformation_);</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160; </div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;  deinitCompute ();</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;}</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160; </div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160; </div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00232"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#af9a399e9cc72e413f9ce769ce4896e10">  232</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::initCompute</a> ()</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;{</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;  std::srand (<span class="keyword">static_cast &lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span> (std::time (NULL)));</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160; </div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;  <span class="comment">// basic pcl initialization</span></div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase &lt;PointSource&gt;::initCompute</a> ())</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160; </div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;  <span class="comment">// check if source and target are given</span></div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;  <span class="keywordflow">if</span> (!input_ || !target_)</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;  {</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[%s::initCompute] Source or target dataset not given!\n&quot;</span>, reg_name_.c_str ());</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;  }</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160; </div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;  <span class="keywordflow">if</span> (!target_indices_ || target_indices_-&gt;size () == 0)</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;  {</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    target_indices_.reset (<span class="keyword">new</span> std::vector &lt;int&gt; (<span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (target_-&gt;size ())));</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;    <span class="keywordtype">int</span> index = 0;</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    <span class="keywordflow">for</span> (std::vector &lt;int&gt;::iterator it = target_indices_-&gt;begin (), it_e = target_indices_-&gt;end (); it != it_e; it++)</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;      *it = index++;</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    target_cloud_updated_ = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;  }</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160; </div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;  <span class="comment">// if a sample size for the point clouds is given; prefarably no sampling of target cloud</span></div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;  <span class="keywordflow">if</span> (nr_samples_ != 0)</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;  {</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> ss = <span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (indices_-&gt;size ());</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> sample_fraction_src = std::max (1, <span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (ss / nr_samples_));</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160; </div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    source_indices_ = pcl::IndicesPtr (<span class="keyword">new</span> std::vector &lt;int&gt;);</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; ss; i++)</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;    <span class="keywordflow">if</span> (rand () % sample_fraction_src == 0)</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;      source_indices_-&gt;push_back ((*indices_) [i]);</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;  }</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    source_indices_ = indices_;</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160; </div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;  <span class="comment">// check usage of normals</span></div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;  <span class="keywordflow">if</span> (source_normals_ &amp;&amp; target_normals_  &amp;&amp; source_normals_-&gt;size () == input_-&gt;size () &amp;&amp; target_normals_-&gt;size () == target_-&gt;size ())</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    use_normals_ = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160; </div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;  <span class="comment">// set up tree structures</span></div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;  <span class="keywordflow">if</span> (target_cloud_updated_)</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;  {</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;    tree_-&gt;setInputCloud (target_, target_indices_);</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;    target_cloud_updated_ = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;  }</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160; </div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;  <span class="comment">// set predefined variables</span></div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> min_iterations = 4;</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span> diameter_fraction = 0.3f;</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160; </div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;  <span class="comment">// get diameter of input cloud (distance between farthest points)</span></div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;  Eigen::Vector4f pt_min, pt_max;</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;  <a class="code" href="group__common.html#ga3166f09aafd659f69dc75e63f5e10f81">pcl::getMinMax3D</a> (*target_, *target_indices_, pt_min, pt_max);</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;  diameter_ = (pt_max - pt_min).norm ();</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160; </div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;  <span class="comment">// derive the limits for the random base selection</span></div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;  <span class="keywordtype">float</span> max_base_diameter = diameter_* approx_overlap_ * 2.f;</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;  max_base_diameter_sqr_ = max_base_diameter * max_base_diameter;</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160; </div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;  <span class="comment">// normalize the delta</span></div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;  <span class="keywordflow">if</span> (normalize_delta_)</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;  {</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    <span class="keywordtype">float</span> mean_dist = getMeanPointDensity &lt;PointTarget&gt; (target_, *target_indices_, 0.05f * diameter_, nr_threads_);</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;    delta_ *= mean_dist;</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;  }</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160; </div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;  <span class="comment">// heuristic determination of number of trials to have high probabilty of finding a good solution</span></div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;  <span class="keywordflow">if</span> (max_iterations_ == 0)</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;  {</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    <span class="keywordtype">float</span> first_est = std::log (small_error_) / std::log (1.0 - std::pow ((<span class="keywordtype">double</span>) approx_overlap_, (<span class="keywordtype">double</span>) min_iterations));</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    max_iterations_ = <span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (first_est / (diameter_fraction * approx_overlap_ * 2.f));</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;  }</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160; </div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;  <span class="comment">// set further parameter</span></div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;  <span class="keywordflow">if</span> (score_threshold_ == FLT_MAX)</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;    score_threshold_ = 1.f - approx_overlap_;</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160; </div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;  <span class="keywordflow">if</span> (max_iterations_ &lt; 4)</div>
<div class="line"><a name="l00313"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ab2c4309ae91b6c3bc6f5480cad22ec67">  313</a></span>&#160;    max_iterations_ = 4;</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160; </div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;  <span class="keywordflow">if</span> (max_runtime_ &lt; 1)</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    max_runtime_ = INT_MAX;</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160; </div>
<div class="line"><a name="l00318"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#af9a399e9cc72e413f9ce769ce4896e10">  318</a></span>&#160;  <span class="comment">// calculate internal parameters based on the the estimated point density</span></div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;  max_pair_diff_ = delta_ * 2.f;</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;  max_edge_diff_ = delta_ * 4.f;</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;  coincidation_limit_ = delta_ * 2.f; <span class="comment">// EDITED: originally std::sqrt (delta_ * 2.f)</span></div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;  max_mse_ = powf (delta_* 2.f, 2.f);</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;  max_inlier_dist_sqr_ = powf (delta_ * 2.f, 2.f);</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160; </div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;  <span class="comment">// reset fitness_score</span></div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;  fitness_score_ = FLT_MAX;</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160; </div>
<div class="line"><a name="l00328"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac34b9f119a6d69a1b7a646bdb8e8dace">  328</a></span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;}</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160; </div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160; </div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00334"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac34b9f119a6d69a1b7a646bdb8e8dace">  334</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::selectBase</a> (</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;  std::vector &lt;int&gt; &amp;base_indices,</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;  float (&amp;ratio)[2])</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;{</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span> too_close_sqr = max_base_diameter_sqr_*0.01;</div>
<div class="line"><a name="l00339"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a16ab9f8757cec569bb0f38544141df7f">  339</a></span>&#160; </div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;  Eigen::VectorXf coefficients (4);</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;  <a class="code" href="classpcl_1_1_sample_consensus_model_plane.html">pcl::SampleConsensusModelPlane &lt;PointTarget&gt;</a> plane (target_);</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;  plane.setIndices (target_indices_);</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;  Eigen::Vector4f centre_pt;</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;  <span class="keywordtype">float</span> nearest_to_plane = FLT_MAX;</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160; </div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;  <span class="comment">// repeat base search until valid quadruple was found or ransac_iterations_ number of trys were unsuccessfull</span></div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; ransac_iterations_; i++)</div>
<div class="line"><a name="l00348"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a607d3bf724f8304008a8e35a6b0a64c8">  348</a></span>&#160;  {</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    <span class="comment">// random select an appropriate point triple</span></div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;    <span class="keywordflow">if</span> (selectBaseTriangle (base_indices) &lt; 0)</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160; </div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    std::vector &lt;int&gt; base_triple (base_indices.begin (), base_indices.end () - 1);</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;    plane.computeModelCoefficients (base_triple, coefficients);</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;    <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a> (*target_, base_triple, centre_pt);</div>
<div class="line"><a name="l00356"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac421e4c56100d9e5a2355252eb9a3643">  356</a></span>&#160; </div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;    <span class="comment">// loop over all points in source cloud to find most suitable fourth point</span></div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;    <span class="keyword">const</span> PointTarget *pt1 = &amp;(target_-&gt;points[base_indices[0]]);</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;    <span class="keyword">const</span> PointTarget *pt2 = &amp;(target_-&gt;points[base_indices[1]]);</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;    <span class="keyword">const</span> PointTarget *pt3 = &amp;(target_-&gt;points[base_indices[2]]);</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160; </div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;    <span class="keywordflow">for</span> (std::vector &lt;int&gt;::iterator it = target_indices_-&gt;begin (), it_e = target_indices_-&gt;end (); it != it_e; it++)</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;    {</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;      <span class="keyword">const</span> PointTarget *pt4 = &amp;(target_-&gt;points[*it]);</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160; </div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;      <span class="keywordtype">float</span> d1 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a28ecc173df18d9175dee9f4dd042390b">pcl::squaredEuclideanDistance</a> (*pt4, *pt1);</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;      <span class="keywordtype">float</span> d2 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a28ecc173df18d9175dee9f4dd042390b">pcl::squaredEuclideanDistance</a> (*pt4, *pt2);</div>
<div class="line"><a name="l00368"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a1392b97316249b70eddde0428ca317c9">  368</a></span>&#160;      <span class="keywordtype">float</span> d3 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a28ecc173df18d9175dee9f4dd042390b">pcl::squaredEuclideanDistance</a> (*pt4, *pt3);</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;      <span class="keywordtype">float</span> d4 = (pt4-&gt;getVector3fMap ()  - centre_pt.head (3)).squaredNorm ();</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160; </div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;      <span class="comment">// check distance between points w.r.t minimum sampling distance; EDITED -&gt; 4th point now also limited by max base line</span></div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;      <span class="keywordflow">if</span> (d1 &lt; too_close_sqr || d2 &lt; too_close_sqr || d3 &lt; too_close_sqr || d4 &lt; too_close_sqr ||</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;        d1 &gt; max_base_diameter_sqr_ || d2 &gt; max_base_diameter_sqr_ || d3 &gt; max_base_diameter_sqr_)</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160; </div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;      <span class="comment">// check distance to plane to get point closest to plane</span></div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;      <span class="keywordtype">float</span> dist_to_plane = pcl::pointToPlaneDistance (*pt4, coefficients);</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;      <span class="keywordflow">if</span> (dist_to_plane &lt; nearest_to_plane)</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;      {</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;        base_indices[3] = *it;</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;        nearest_to_plane = dist_to_plane;</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;      }</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;    }</div>
<div class="line"><a name="l00384"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a37b21d4669718973b6ab1aa8936a1704">  384</a></span>&#160; </div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;    <span class="comment">// check if at least one point fullfilled the conditions</span></div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;    <span class="keywordflow">if</span> (nearest_to_plane != FLT_MAX)</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;    {</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;      <span class="comment">// order points to build largest quadrangle and calcuate intersection ratios of diagonals</span></div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;      setupBase (base_indices, ratio);</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;      <span class="keywordflow">return</span> (0);</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;    }</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;  }</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160; </div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;  <span class="comment">// return unsuccessfull if no quadruple was selected</span></div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;  <span class="keywordflow">return</span> (-1);</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;}</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160; </div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160; </div>
<div class="line"><a name="l00400"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac6ccba63325f96f5e38fc065b0897ea3">  400</a></span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00401"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a16ab9f8757cec569bb0f38544141df7f">  401</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::selectBaseTriangle</a> (std::vector &lt;int&gt; &amp;base_indices)</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;{</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;  <span class="keywordtype">int</span> nr_points = <span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (target_indices_-&gt;size ());</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;  <span class="keywordtype">float</span> best_t = 0.f;</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160; </div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;  <span class="comment">// choose random first point</span></div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;  base_indices[0] = (*target_indices_)[rand () % nr_points];</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;  <span class="keywordtype">int</span> *index1 = &amp;base_indices[0];</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160; </div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;  <span class="comment">// random search for 2 other points (as far away as overlap allows)</span></div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; ransac_iterations_; i++)</div>
<div class="line"><a name="l00412"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a0d59c76f9a58f59caf2b63e377aca6bb">  412</a></span>&#160;  {</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;    <span class="keywordtype">int</span> *index2 = &amp;(*target_indices_)[rand () % nr_points];</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;    <span class="keywordtype">int</span> *index3 = &amp;(*target_indices_)[rand () % nr_points];</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160; </div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;    Eigen::Vector3f u = target_-&gt;points[*index2].getVector3fMap () - target_-&gt;points[*index1].getVector3fMap ();</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;    Eigen::Vector3f v = target_-&gt;points[*index3].getVector3fMap () - target_-&gt;points[*index1].getVector3fMap ();</div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;    <span class="keywordtype">float</span> t = u.cross (v).squaredNorm (); <span class="comment">// triangle area (0.5 * sqrt(t)) should be maximal</span></div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160; </div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;    <span class="comment">// check for most suitable point triple</span></div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;    <span class="keywordflow">if</span> (t &gt; best_t &amp;&amp; u.squaredNorm () &lt; max_base_diameter_sqr_ &amp;&amp; v.squaredNorm () &lt; max_base_diameter_sqr_)</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;    {</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;      best_t = t;</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;      base_indices[1] = *index2;</div>
<div class="line"><a name="l00425"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ab5b94e6b02f11c17f4b10af2c89f6228">  425</a></span>&#160;      base_indices[2] = *index3;</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;    }</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;  }</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160; </div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;  <span class="comment">// return if a triplet could be selected</span></div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;  <span class="keywordflow">return</span> (best_t == 0.f ? -1 : 0);</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;}</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160; </div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160; </div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00436"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a607d3bf724f8304008a8e35a6b0a64c8">  436</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::setupBase</a> (</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;  std::vector &lt;int&gt; &amp;base_indices,</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;  float (&amp;ratio)[2])</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;{</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;  <span class="keywordtype">float</span> best_t = FLT_MAX;</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; copy (base_indices.begin (), base_indices.end ());</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;  std::vector &lt;int&gt; temp (base_indices.begin (), base_indices.end ());</div>
<div class="line"><a name="l00443"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac63173082b064d29ac50cee964ec930e">  443</a></span>&#160; </div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;  <span class="comment">// loop over all combinations of base points</span></div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;  <span class="keywordflow">for</span> (std::vector &lt;int&gt;::const_iterator i = copy.begin (), i_e = copy.end (); i != i_e; i++)</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;  <span class="keywordflow">for</span> (std::vector &lt;int&gt;::const_iterator j = copy.begin (), j_e = copy.end (); j != j_e; j++)</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;  {</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    <span class="keywordflow">if</span> (i == j)</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160; </div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;    <span class="keywordflow">for</span> (std::vector &lt;int&gt;::const_iterator k = copy.begin (), k_e = copy.end (); k != k_e; k++)</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;    {</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;      <span class="keywordflow">if</span> (k == j || k == i)</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160; </div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;      std::vector &lt;int&gt;::const_iterator l = copy.begin ();</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;      <span class="keywordflow">while</span> (l == i || l == j || l == k)</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;        l++;</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160; </div>
<div class="line"><a name="l00460"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a2e628406e7a4bfbc06754fc89da60c2b">  460</a></span>&#160;      temp[0] = *i;</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;      temp[1] = *j;</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;      temp[2] = *k;</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;      temp[3] = *l;</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160; </div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;      <span class="comment">// calculate diagonal intersection ratios and check for suitable segment to segment distances</span></div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;      <span class="keywordtype">float</span> ratio_temp[2];</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;      <span class="keywordtype">float</span> t = segmentToSegmentDist (temp, ratio_temp);</div>
<div class="line"><a name="l00468"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a0182f309b73f20835d5ca7356fa167dc">  468</a></span>&#160;      <span class="keywordflow">if</span> (t &lt; best_t)</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;      {</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;        best_t = t;</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;        ratio[0] = ratio_temp[0];</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;        ratio[1] = ratio_temp[1];</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;        base_indices = temp;</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;      }</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;    }</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;  }</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;}</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160; </div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160; </div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">float</span></div>
<div class="line"><a name="l00482"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac421e4c56100d9e5a2355252eb9a3643">  482</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::segmentToSegmentDist</a> (</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; &amp;base_indices,</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;  float (&amp;ratio)[2])</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;{</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;  <span class="comment">// get point vectors</span></div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;  Eigen::Vector3f u = target_-&gt;points[base_indices[1]].getVector3fMap () - target_-&gt;points[base_indices[0]].getVector3fMap ();</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;  Eigen::Vector3f v = target_-&gt;points[base_indices[3]].getVector3fMap () - target_-&gt;points[base_indices[2]].getVector3fMap ();</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;  Eigen::Vector3f w = target_-&gt;points[base_indices[0]].getVector3fMap () - target_-&gt;points[base_indices[2]].getVector3fMap ();</div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160; </div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;  <span class="comment">// calculate segment distances</span></div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;  <span class="keywordtype">float</span> a = u.dot (u);</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;  <span class="keywordtype">float</span> b = u.dot (v);</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;  <span class="keywordtype">float</span> c = v.dot (v);</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;  <span class="keywordtype">float</span> d = u.dot (w);</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;  <span class="keywordtype">float</span> e = v.dot (w);</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;  <span class="keywordtype">float</span> D = a * c - b * b;</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;  <span class="keywordtype">float</span> sN = 0.f, sD = D;</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;  <span class="keywordtype">float</span> tN = 0.f, tD = D;</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160; </div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;  <span class="comment">// check segments</span></div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;  <span class="keywordflow">if</span> (D &lt; small_error_)</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;  {</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;    sN = 0.f;</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;    sD = 1.f;</div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;    tN = e;</div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;    tD = c;</div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;  }</div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;  {</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;    sN = (b * e - c * d);</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;    tN = (a * e - b * d);</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160; </div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;    <span class="keywordflow">if</span> (sN &lt; 0.f)</div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;    {</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;      sN = 0.f;</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;      tN = e;</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;      tD = c;</div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;    }</div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;    <span class="keywordflow">else</span> <span class="keywordflow">if</span> (sN &gt; sD)</div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;    {</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;      sN = sD;</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;      tN = e + b;</div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;      tD = c;</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;    }</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;  }</div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160; </div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;  <span class="keywordflow">if</span> (tN &lt; 0.f)</div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;  {</div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;    tN = 0.f;</div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160; </div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;    <span class="keywordflow">if</span> (-d &lt; 0.f)</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;      sN = 0.f;</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160; </div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;    <span class="keywordflow">else</span> <span class="keywordflow">if</span> (-d &gt; a)</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;      sN = sD;</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160; </div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;    {</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;      sN = -d;</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;      sD = a;</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;    }</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;  }</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160; </div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (tN &gt; tD)</div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;  {</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;    tN = tD;</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160; </div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;    <span class="keywordflow">if</span> ((-d + b) &lt; 0.f)</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;      sN = 0.f;</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160; </div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;    <span class="keywordflow">else</span> <span class="keywordflow">if</span> ((-d + b) &gt; a)</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;      sN = sD;</div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160; </div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;    {</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;      sN = (-d + b);</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;      sD = a;</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;    }</div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;  }</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160; </div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;  <span class="comment">// set intersection ratios</span></div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;  ratio[0] = (std::abs (sN) &lt; small_error_) ? 0.f : sN / sD;</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;  ratio[1] = (std::abs (tN) &lt; small_error_) ? 0.f : tN / tD;</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160; </div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;  Eigen::Vector3f x = w + (ratio[0] * u) - (ratio[1] * v);</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;  <span class="keywordflow">return</span> (x.norm ());</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;}</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160; </div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160; </div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00573"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a1392b97316249b70eddde0428ca317c9">  573</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::bruteForceCorrespondences</a> (</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;  <span class="keywordtype">int</span> idx1,</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;  <span class="keywordtype">int</span> idx2,</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;  pcl::Correspondences &amp;pairs)</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;{</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span> max_norm_diff = 0.5f * max_norm_diff_ * M_PI / 180.f;</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160; </div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;  <span class="comment">// calculate reference segment distance and normal angle</span></div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;  <span class="keywordtype">float</span> ref_dist = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (target_-&gt;points[idx1], target_-&gt;points[idx2]);</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;  <span class="keywordtype">float</span> ref_norm_angle = (use_normals_ ? (target_normals_-&gt;points[idx1].getNormalVector3fMap () -</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;                                          target_normals_-&gt;points[idx2].getNormalVector3fMap ()).norm () : 0.f);</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160; </div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;  <span class="comment">// loop over all pairs of points in source point cloud</span></div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;  std::vector &lt;int&gt;::iterator it_out = source_indices_-&gt;begin (), it_out_e = source_indices_-&gt;end () - 1;</div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;  std::vector &lt;int&gt;::iterator it_in, it_in_e = source_indices_-&gt;end ();</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;  <span class="keywordflow">for</span> ( ; it_out != it_out_e; it_out++)</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;  {</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;    it_in = it_out + 1;</div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;    <span class="keyword">const</span> PointSource *pt1 = &amp;(*input_)[*it_out];</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;    <span class="keywordflow">for</span> ( ; it_in != it_in_e; it_in++)</div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;    {</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;      <span class="keyword">const</span> PointSource *pt2 = &amp;(*input_)[*it_in];</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160; </div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;      <span class="comment">// check point distance compared to reference dist (from base)</span></div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;      <span class="keywordtype">float</span> dist = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (*pt1, *pt2);</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;      <span class="keywordflow">if</span> (std::abs(dist - ref_dist) &lt; max_pair_diff_)</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;      {</div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;        <span class="comment">// add here normal evaluation if normals are given</span></div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;        <span class="keywordflow">if</span> (use_normals_)</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;        {</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;          <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> *pt1_n = &amp;(source_normals_-&gt;points[*it_out]);</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;          <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> *pt2_n = &amp;(source_normals_-&gt;points[*it_in]);</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160; </div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;          <span class="keywordtype">float</span> norm_angle_1 = (pt1_n-&gt;getNormalVector3fMap () - pt2_n-&gt;getNormalVector3fMap ()).norm ();</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;          <span class="keywordtype">float</span> norm_angle_2 = (pt1_n-&gt;getNormalVector3fMap () + pt2_n-&gt;getNormalVector3fMap ()).norm ();</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160; </div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;          <span class="keywordtype">float</span> norm_diff = std::min &lt;float&gt; (std::abs (norm_angle_1 - ref_norm_angle), std::abs (norm_angle_2 - ref_norm_angle));</div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;          <span class="keywordflow">if</span> (norm_diff &gt; max_norm_diff)</div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;            <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;        }</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160; </div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;        pairs.push_back (<a class="code" href="structpcl_1_1_correspondence.html">pcl::Correspondence</a> (*it_in, *it_out, dist));</div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;        pairs.push_back (<a class="code" href="structpcl_1_1_correspondence.html">pcl::Correspondence</a> (*it_out, *it_in, dist));</div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;      }</div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;    }</div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;  }</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160; </div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;  <span class="comment">// return success if at least one correspondence was found</span></div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;  <span class="keywordflow">return</span> (pairs.size () == 0 ? -1 : 0);</div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;}</div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160; </div>
<div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160; </div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00627"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a37b21d4669718973b6ab1aa8936a1704">  627</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::determineBaseMatches</a> (</div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; &amp;base_indices,</div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160;  std::vector &lt;std::vector &lt;int&gt; &gt; &amp;matches,</div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;  <span class="keyword">const</span> pcl::Correspondences &amp;pairs_a,</div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;  <span class="keyword">const</span> pcl::Correspondences &amp;pairs_b,</div>
<div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;  <span class="keyword">const</span> float (&amp;ratio)[2])</div>
<div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;{</div>
<div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;  <span class="comment">// calculate edge lengths of base</span></div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;  <span class="keywordtype">float</span> dist_base[4];</div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;  dist_base[0] = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (target_-&gt;points[base_indices[0]], target_-&gt;points[base_indices[2]]);</div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;  dist_base[1] = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (target_-&gt;points[base_indices[0]], target_-&gt;points[base_indices[3]]);</div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;  dist_base[2] = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (target_-&gt;points[base_indices[1]], target_-&gt;points[base_indices[2]]);</div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160;  dist_base[3] = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (target_-&gt;points[base_indices[1]], target_-&gt;points[base_indices[3]]);</div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160; </div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;  <span class="comment">// loop over first point pair correspondences and store intermediate points &#39;e&#39; in new point cloud</span></div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;  PointCloudSourcePtr cloud_e (<span class="keyword">new</span> PointCloudSource);</div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;  cloud_e-&gt;resize (pairs_a.size () * 2);</div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;  PointCloudSourceIterator it_pt = cloud_e-&gt;begin ();</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;  <span class="keywordflow">for</span> (pcl::Correspondences::const_iterator it_pair = pairs_a.begin (), it_pair_e = pairs_a.end () ; it_pair != it_pair_e; it_pair++)</div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;  {</div>
<div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;    <span class="keyword">const</span> PointSource *pt1 = &amp;(input_-&gt;points[it_pair-&gt;index_match]);</div>
<div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;    <span class="keyword">const</span> PointSource *pt2 = &amp;(input_-&gt;points[it_pair-&gt;index_query]);</div>
<div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160; </div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;    <span class="comment">// calculate intermediate points using both ratios from base (r1,r2)</span></div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 2; i++, it_pt++)</div>
<div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;    {</div>
<div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;      it_pt-&gt;x = pt1-&gt;x + ratio[i] * (pt2-&gt;x - pt1-&gt;x);</div>
<div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160;      it_pt-&gt;y = pt1-&gt;y + ratio[i] * (pt2-&gt;y - pt1-&gt;y);</div>
<div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;      it_pt-&gt;z = pt1-&gt;z + ratio[i] * (pt2-&gt;z - pt1-&gt;z);</div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;    }</div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;  }</div>
<div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160; </div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;  <span class="comment">// initialize new kd tree of intermediate points from first point pair correspondences</span></div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;  KdTreeReciprocalPtr tree_e (<span class="keyword">new</span> <a class="code" href="classpcl_1_1search_1_1_kd_tree.html">KdTreeReciprocal</a>);</div>
<div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;  tree_e-&gt;setInputCloud (cloud_e);</div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160; </div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;  std::vector &lt;int&gt; ids;</div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;  std::vector &lt;float&gt; dists_sqr;</div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160; </div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;  <span class="comment">// loop over second point pair correspondences</span></div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;  <span class="keywordflow">for</span> (pcl::Correspondences::const_iterator it_pair = pairs_b.begin (), it_pair_e = pairs_b.end () ; it_pair != it_pair_e; it_pair++)</div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;  {</div>
<div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;    <span class="keyword">const</span> PointTarget *pt1 = &amp;(input_-&gt;points[it_pair-&gt;index_match]);</div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;    <span class="keyword">const</span> PointTarget *pt2 = &amp;(input_-&gt;points[it_pair-&gt;index_query]);</div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160; </div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;    <span class="comment">// calculate intermediate points using both ratios from base (r1,r2)</span></div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 2; i++)</div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;    {</div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;      PointTarget pt_e;</div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;      pt_e.x = pt1-&gt;x + ratio[i] * (pt2-&gt;x - pt1-&gt;x);</div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;      pt_e.y = pt1-&gt;y + ratio[i] * (pt2-&gt;y - pt1-&gt;y);</div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;      pt_e.z = pt1-&gt;z + ratio[i] * (pt2-&gt;z - pt1-&gt;z);</div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160; </div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;      <span class="comment">// search for corresponding intermediate points</span></div>
<div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;      tree_e-&gt;radiusSearch (pt_e, coincidation_limit_, ids, dists_sqr);</div>
<div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;      <span class="keywordflow">for</span> (std::vector &lt;int&gt;::iterator it = ids.begin (), it_e = ids.end (); it != it_e; it++)</div>
<div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;      {</div>
<div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160;        std::vector &lt;int&gt; match_indices (4);</div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160; </div>
<div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160;        match_indices[0] = pairs_a[<span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (std::floor ((<span class="keywordtype">float</span>)(*it/2.f)))].index_match;</div>
<div class="line"><a name="l00687"></a><span class="lineno">  687</span>&#160;        match_indices[1] = pairs_a[<span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (std::floor ((<span class="keywordtype">float</span>)(*it/2.f)))].index_query;</div>
<div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;        match_indices[2] = it_pair-&gt;index_match;</div>
<div class="line"><a name="l00689"></a><span class="lineno">  689</span>&#160;        match_indices[3] = it_pair-&gt;index_query;</div>
<div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160; </div>
<div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;        <span class="comment">// EDITED: added coarse check of match based on edge length (due to rigid-body )</span></div>
<div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;        <span class="keywordflow">if</span> (checkBaseMatch (match_indices, dist_base) &lt; 0)</div>
<div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;          <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160; </div>
<div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;        matches.push_back (match_indices);</div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;      }</div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160;    }</div>
<div class="line"><a name="l00698"></a><span class="lineno">  698</span>&#160;  }</div>
<div class="line"><a name="l00699"></a><span class="lineno">  699</span>&#160; </div>
<div class="line"><a name="l00700"></a><span class="lineno">  700</span>&#160;  <span class="comment">// return unsuccessfull if no match was found</span></div>
<div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;  <span class="keywordflow">return</span> (matches.size () &gt; 0 ? 0 : -1);</div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;}</div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160; </div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160; </div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00707"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac6ccba63325f96f5e38fc065b0897ea3">  707</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::checkBaseMatch</a> (</div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; &amp;match_indices,</div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;  <span class="keyword">const</span> float (&amp;dist_ref)[4])</div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;{</div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;  <span class="keywordtype">float</span> d0 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (input_-&gt;points[match_indices[0]], input_-&gt;points[match_indices[2]]);</div>
<div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160;  <span class="keywordtype">float</span> d1 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (input_-&gt;points[match_indices[0]], input_-&gt;points[match_indices[3]]);</div>
<div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160;  <span class="keywordtype">float</span> d2 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (input_-&gt;points[match_indices[1]], input_-&gt;points[match_indices[2]]);</div>
<div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;  <span class="keywordtype">float</span> d3 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a> (input_-&gt;points[match_indices[1]], input_-&gt;points[match_indices[3]]);</div>
<div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160; </div>
<div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;  <span class="comment">// check edge distances of match w.r.t the base</span></div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;  <span class="keywordflow">return</span> (std::abs (d0 - dist_ref[0]) &lt; max_edge_diff_ &amp;&amp; std::abs (d1 - dist_ref[1]) &lt; max_edge_diff_ &amp;&amp;</div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;          std::abs (d2 - dist_ref[2]) &lt; max_edge_diff_ &amp;&amp; std::abs (d3 - dist_ref[3]) &lt; max_edge_diff_) ? 0 : -1;</div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;}</div>
<div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160; </div>
<div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160; </div>
<div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00724"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a0d59c76f9a58f59caf2b63e377aca6bb">  724</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::handleMatches</a> (</div>
<div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; &amp;base_indices,</div>
<div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;  std::vector &lt;std::vector &lt;int&gt; &gt; &amp;matches,</div>
<div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;  MatchingCandidates &amp;candidates)</div>
<div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;{</div>
<div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160;  candidates.resize (1);</div>
<div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;  <span class="keywordtype">float</span> fitness_score = FLT_MAX;</div>
<div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160; </div>
<div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160;  <span class="comment">// loop over all Candidate matches</span></div>
<div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;  <span class="keywordflow">for</span> (std::vector &lt;std::vector &lt;int&gt; &gt;::iterator match_indices = matches.begin (), it_e = matches.end (); match_indices != it_e; match_indices++)</div>
<div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;  {</div>
<div class="line"><a name="l00735"></a><span class="lineno">  735</span>&#160;    Eigen::Matrix4f transformation_temp;</div>
<div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;    pcl::Correspondences correspondences_temp;</div>
<div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160; </div>
<div class="line"><a name="l00738"></a><span class="lineno">  738</span>&#160;    <span class="comment">// determine corresondences between base and match according to their distance to centroid</span></div>
<div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160;    linkMatchWithBase (base_indices, *match_indices, correspondences_temp);</div>
<div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160; </div>
<div class="line"><a name="l00741"></a><span class="lineno">  741</span>&#160;    <span class="comment">// check match based on residuals of the corresponding points after</span></div>
<div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;    <span class="keywordflow">if</span> (validateMatch (base_indices, *match_indices, correspondences_temp, transformation_temp) &lt; 0)</div>
<div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160; </div>
<div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160;    <span class="comment">// check resulting  using a sub sample of the source point cloud and compare to previous matches</span></div>
<div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;    <span class="keywordflow">if</span> (validateTransformation (transformation_temp, fitness_score) &lt; 0)</div>
<div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160; </div>
<div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;    <span class="comment">// store best match as well as associated fitness_score and transformation</span></div>
<div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;    candidates[0].fitness_score = fitness_score;</div>
<div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;    candidates [0].transformation = transformation_temp;</div>
<div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;    correspondences_temp.erase (correspondences_temp.end () - 1);</div>
<div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;    candidates[0].correspondences = correspondences_temp;</div>
<div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;  }</div>
<div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;}</div>
<div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160; </div>
<div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160; </div>
<div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00760"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ab5b94e6b02f11c17f4b10af2c89f6228">  760</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::linkMatchWithBase</a> (</div>
<div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; &amp;base_indices,</div>
<div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;  std::vector &lt;int&gt; &amp;match_indices,</div>
<div class="line"><a name="l00763"></a><span class="lineno">  763</span>&#160;  pcl::Correspondences &amp;correspondences)</div>
<div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;{</div>
<div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160;  <span class="comment">// calculate centroid of base and target</span></div>
<div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;  Eigen::Vector4f centre_base, centre_match;</div>
<div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a> (*target_, base_indices, centre_base);</div>
<div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a> (*input_, match_indices, centre_match);</div>
<div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160; </div>
<div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;  PointTarget centre_pt_base;</div>
<div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;  centre_pt_base.x = centre_base[0];</div>
<div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;  centre_pt_base.y = centre_base[1];</div>
<div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;  centre_pt_base.z = centre_base[2];</div>
<div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160; </div>
<div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160;  PointSource centre_pt_match;</div>
<div class="line"><a name="l00776"></a><span class="lineno">  776</span>&#160;  centre_pt_match.x = centre_match[0];</div>
<div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;  centre_pt_match.y = centre_match[1];</div>
<div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;  centre_pt_match.z = centre_match[2];</div>
<div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160; </div>
<div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;  <span class="comment">// find corresponding points according to their distance to the centroid</span></div>
<div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160;  std::vector &lt;int&gt; copy = match_indices;</div>
<div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160; </div>
<div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;  std::vector &lt;int&gt;::const_iterator it_base = base_indices.begin (), it_base_e = base_indices.end ();</div>
<div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;  std::vector &lt;int&gt;::iterator it_match, it_match_e = copy.end ();</div>
<div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;  std::vector &lt;int&gt;::iterator it_match_orig = match_indices.begin ();</div>
<div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;  <span class="keywordflow">for</span> (; it_base != it_base_e; it_base++, it_match_orig++)</div>
<div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;  {</div>
<div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;    <span class="keywordtype">float</span> dist_sqr_1 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a28ecc173df18d9175dee9f4dd042390b">pcl::squaredEuclideanDistance</a> (target_-&gt;points[*it_base], centre_pt_base);</div>
<div class="line"><a name="l00789"></a><span class="lineno">  789</span>&#160;    <span class="keywordtype">float</span> best_diff_sqr = FLT_MAX;</div>
<div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160;    <span class="keywordtype">int</span> best_index;</div>
<div class="line"><a name="l00791"></a><span class="lineno">  791</span>&#160; </div>
<div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;    <span class="keywordflow">for</span> (it_match = copy.begin (); it_match != it_match_e; it_match++)</div>
<div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160;    {</div>
<div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;      <span class="comment">// calculate difference of distances to centre point</span></div>
<div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;      <span class="keywordtype">float</span> dist_sqr_2 = <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a28ecc173df18d9175dee9f4dd042390b">pcl::squaredEuclideanDistance</a> (input_-&gt;points[*it_match], centre_pt_match);</div>
<div class="line"><a name="l00796"></a><span class="lineno">  796</span>&#160;      <span class="keywordtype">float</span> diff_sqr = std::abs(dist_sqr_1 - dist_sqr_2);</div>
<div class="line"><a name="l00797"></a><span class="lineno">  797</span>&#160; </div>
<div class="line"><a name="l00798"></a><span class="lineno">  798</span>&#160;      <span class="keywordflow">if</span> (diff_sqr &lt; best_diff_sqr)</div>
<div class="line"><a name="l00799"></a><span class="lineno">  799</span>&#160;      {</div>
<div class="line"><a name="l00800"></a><span class="lineno">  800</span>&#160;        best_diff_sqr = diff_sqr;</div>
<div class="line"><a name="l00801"></a><span class="lineno">  801</span>&#160;        best_index = *it_match;</div>
<div class="line"><a name="l00802"></a><span class="lineno">  802</span>&#160;      }</div>
<div class="line"><a name="l00803"></a><span class="lineno">  803</span>&#160;    }</div>
<div class="line"><a name="l00804"></a><span class="lineno">  804</span>&#160; </div>
<div class="line"><a name="l00805"></a><span class="lineno">  805</span>&#160;    <span class="comment">// assign new correspondence and update indices of matched targets</span></div>
<div class="line"><a name="l00806"></a><span class="lineno">  806</span>&#160;    correspondences.push_back (<a class="code" href="structpcl_1_1_correspondence.html">pcl::Correspondence</a> (best_index, *it_base, best_diff_sqr));</div>
<div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160;    *it_match_orig = best_index;</div>
<div class="line"><a name="l00808"></a><span class="lineno">  808</span>&#160;  }</div>
<div class="line"><a name="l00809"></a><span class="lineno">  809</span>&#160;}</div>
<div class="line"><a name="l00810"></a><span class="lineno">  810</span>&#160; </div>
<div class="line"><a name="l00811"></a><span class="lineno">  811</span>&#160; </div>
<div class="line"><a name="l00813"></a><span class="lineno">  813</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00814"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#ac63173082b064d29ac50cee964ec930e">  814</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::validateMatch</a> (</div>
<div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; &amp;base_indices,</div>
<div class="line"><a name="l00816"></a><span class="lineno">  816</span>&#160;  <span class="keyword">const</span> std::vector &lt;int&gt; &amp;match_indices,</div>
<div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160;  <span class="keyword">const</span> pcl::Correspondences &amp;correspondences,</div>
<div class="line"><a name="l00818"></a><span class="lineno">  818</span>&#160;  Eigen::Matrix4f &amp;transformation)</div>
<div class="line"><a name="l00819"></a><span class="lineno">  819</span>&#160;{</div>
<div class="line"><a name="l00820"></a><span class="lineno">  820</span>&#160;  <span class="comment">// only use triplet of points to simlify process (possible due to planar case)</span></div>
<div class="line"><a name="l00821"></a><span class="lineno">  821</span>&#160;  pcl::Correspondences correspondences_temp = correspondences;</div>
<div class="line"><a name="l00822"></a><span class="lineno">  822</span>&#160;  correspondences_temp.erase (correspondences_temp.end () - 1);</div>
<div class="line"><a name="l00823"></a><span class="lineno">  823</span>&#160; </div>
<div class="line"><a name="l00824"></a><span class="lineno">  824</span>&#160;  <span class="comment">// estimate transformation between correspondence set</span></div>
<div class="line"><a name="l00825"></a><span class="lineno">  825</span>&#160;  transformation_estimation_-&gt;estimateRigidTransformation (*input_, *target_, correspondences_temp, transformation);</div>
<div class="line"><a name="l00826"></a><span class="lineno">  826</span>&#160; </div>
<div class="line"><a name="l00827"></a><span class="lineno">  827</span>&#160;  <span class="comment">// transform base points</span></div>
<div class="line"><a name="l00828"></a><span class="lineno">  828</span>&#160;  PointCloudSource match_transformed;</div>
<div class="line"><a name="l00829"></a><span class="lineno">  829</span>&#160;  <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*input_, match_indices, match_transformed, transformation);</div>
<div class="line"><a name="l00830"></a><span class="lineno">  830</span>&#160; </div>
<div class="line"><a name="l00831"></a><span class="lineno">  831</span>&#160;  <span class="comment">// calculate residuals of transformation and check against maximum threshold</span></div>
<div class="line"><a name="l00832"></a><span class="lineno">  832</span>&#160;  std::size_t nr_points = correspondences_temp.size ();</div>
<div class="line"><a name="l00833"></a><span class="lineno">  833</span>&#160;  <span class="keywordtype">float</span> mse = 0.f;</div>
<div class="line"><a name="l00834"></a><span class="lineno">  834</span>&#160;  <span class="keywordflow">for</span> (std::size_t i = 0; i &lt; nr_points; i++)</div>
<div class="line"><a name="l00835"></a><span class="lineno">  835</span>&#160;    mse += <a class="code" href="common_2include_2pcl_2common_2distances_8h.html#a28ecc173df18d9175dee9f4dd042390b">pcl::squaredEuclideanDistance</a> (match_transformed.points [i], target_-&gt;points [base_indices[i]]);</div>
<div class="line"><a name="l00836"></a><span class="lineno">  836</span>&#160; </div>
<div class="line"><a name="l00837"></a><span class="lineno">  837</span>&#160;  mse /= nr_points;</div>
<div class="line"><a name="l00838"></a><span class="lineno">  838</span>&#160;  <span class="keywordflow">return</span> (mse &lt; max_mse_ ? 0 : -1);</div>
<div class="line"><a name="l00839"></a><span class="lineno">  839</span>&#160;}</div>
<div class="line"><a name="l00840"></a><span class="lineno">  840</span>&#160; </div>
<div class="line"><a name="l00841"></a><span class="lineno">  841</span>&#160; </div>
<div class="line"><a name="l00843"></a><span class="lineno">  843</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00844"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a2e628406e7a4bfbc06754fc89da60c2b">  844</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::validateTransformation</a> (</div>
<div class="line"><a name="l00845"></a><span class="lineno">  845</span>&#160;  Eigen::Matrix4f &amp;transformation,</div>
<div class="line"><a name="l00846"></a><span class="lineno">  846</span>&#160;  <span class="keywordtype">float</span> &amp;fitness_score)</div>
<div class="line"><a name="l00847"></a><span class="lineno">  847</span>&#160;{</div>
<div class="line"><a name="l00848"></a><span class="lineno">  848</span>&#160;  <span class="comment">// transform source point cloud</span></div>
<div class="line"><a name="l00849"></a><span class="lineno">  849</span>&#160;  PointCloudSource source_transformed;</div>
<div class="line"><a name="l00850"></a><span class="lineno">  850</span>&#160;  <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*input_, *source_indices_, source_transformed, transformation);</div>
<div class="line"><a name="l00851"></a><span class="lineno">  851</span>&#160; </div>
<div class="line"><a name="l00852"></a><span class="lineno">  852</span>&#160;  std::size_t nr_points = source_transformed.size ();</div>
<div class="line"><a name="l00853"></a><span class="lineno">  853</span>&#160;  std::size_t terminate_value = fitness_score &gt; 1 ? 0 : <span class="keyword">static_cast &lt;</span>std::size_t<span class="keyword">&gt;</span> ((1.f - fitness_score) * nr_points);</div>
<div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160; </div>
<div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160;  <span class="keywordtype">float</span> inlier_score_temp = 0;</div>
<div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;  std::vector &lt;int&gt; ids;</div>
<div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;  std::vector &lt;float&gt; dists_sqr;</div>
<div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;  PointCloudSourceIterator it = source_transformed.begin ();</div>
<div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160; </div>
<div class="line"><a name="l00860"></a><span class="lineno">  860</span>&#160;  <span class="keywordflow">for</span> (std::size_t i = 0; i &lt; nr_points; it++, i++)</div>
<div class="line"><a name="l00861"></a><span class="lineno">  861</span>&#160;  {</div>
<div class="line"><a name="l00862"></a><span class="lineno">  862</span>&#160;    <span class="comment">// search for nearest point using kd tree search</span></div>
<div class="line"><a name="l00863"></a><span class="lineno">  863</span>&#160;    tree_-&gt;nearestKSearch (*it, 1, ids, dists_sqr);</div>
<div class="line"><a name="l00864"></a><span class="lineno">  864</span>&#160;    inlier_score_temp += (dists_sqr[0] &lt; max_inlier_dist_sqr_ ? 1 : 0);</div>
<div class="line"><a name="l00865"></a><span class="lineno">  865</span>&#160; </div>
<div class="line"><a name="l00866"></a><span class="lineno">  866</span>&#160;    <span class="comment">// early terminating</span></div>
<div class="line"><a name="l00867"></a><span class="lineno">  867</span>&#160;    <span class="keywordflow">if</span> (nr_points - i + inlier_score_temp &lt; terminate_value)</div>
<div class="line"><a name="l00868"></a><span class="lineno">  868</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00869"></a><span class="lineno">  869</span>&#160;  }</div>
<div class="line"><a name="l00870"></a><span class="lineno">  870</span>&#160; </div>
<div class="line"><a name="l00871"></a><span class="lineno">  871</span>&#160;  <span class="comment">// check current costs and return unsuccessfull if larger than previous ones</span></div>
<div class="line"><a name="l00872"></a><span class="lineno">  872</span>&#160;  inlier_score_temp /= <span class="keyword">static_cast &lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (nr_points);</div>
<div class="line"><a name="l00873"></a><span class="lineno">  873</span>&#160;  <span class="keywordtype">float</span> fitness_score_temp = 1.f - inlier_score_temp;</div>
<div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160; </div>
<div class="line"><a name="l00875"></a><span class="lineno">  875</span>&#160;  <span class="keywordflow">if</span> (fitness_score_temp &gt; fitness_score)</div>
<div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;    <span class="keywordflow">return</span> (-1);</div>
<div class="line"><a name="l00877"></a><span class="lineno">  877</span>&#160; </div>
<div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;  fitness_score = fitness_score_temp;</div>
<div class="line"><a name="l00879"></a><span class="lineno">  879</span>&#160;  <span class="keywordflow">return</span> (0);</div>
<div class="line"><a name="l00880"></a><span class="lineno">  880</span>&#160;}</div>
<div class="line"><a name="l00881"></a><span class="lineno">  881</span>&#160; </div>
<div class="line"><a name="l00882"></a><span class="lineno">  882</span>&#160; </div>
<div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target, <span class="keyword">typename</span> NormalT, <span class="keyword">typename</span> Scalar&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00885"></a><span class="lineno"><a class="line" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html#a0182f309b73f20835d5ca7356fa167dc">  885</a></span>&#160;<a class="code" href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment &lt;PointSource, PointTarget, NormalT, Scalar&gt;::finalCompute</a> (</div>
<div class="line"><a name="l00886"></a><span class="lineno">  886</span>&#160;  <span class="keyword">const</span> std::vector &lt;MatchingCandidates &gt; &amp;candidates)</div>
<div class="line"><a name="l00887"></a><span class="lineno">  887</span>&#160;{</div>
<div class="line"><a name="l00888"></a><span class="lineno">  888</span>&#160;  <span class="comment">// get best fitness_score over all trys</span></div>
<div class="line"><a name="l00889"></a><span class="lineno">  889</span>&#160;  <span class="keywordtype">int</span> nr_candidates = <span class="keyword">static_cast &lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (candidates.size ());</div>
<div class="line"><a name="l00890"></a><span class="lineno">  890</span>&#160;  <span class="keywordtype">int</span> best_index = -1;</div>
<div class="line"><a name="l00891"></a><span class="lineno">  891</span>&#160;  <span class="keywordtype">float</span> best_score = FLT_MAX;</div>
<div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; nr_candidates; i++)</div>
<div class="line"><a name="l00893"></a><span class="lineno">  893</span>&#160;  {</div>
<div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">float</span> &amp;fitness_score = candidates [i][0].fitness_score;</div>
<div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;    <span class="keywordflow">if</span> (fitness_score &lt; best_score)</div>
<div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160;    {</div>
<div class="line"><a name="l00897"></a><span class="lineno">  897</span>&#160;      best_score = fitness_score;</div>
<div class="line"><a name="l00898"></a><span class="lineno">  898</span>&#160;      best_index = i;</div>
<div class="line"><a name="l00899"></a><span class="lineno">  899</span>&#160;    }</div>
<div class="line"><a name="l00900"></a><span class="lineno">  900</span>&#160;  }</div>
<div class="line"><a name="l00901"></a><span class="lineno">  901</span>&#160; </div>
<div class="line"><a name="l00902"></a><span class="lineno">  902</span>&#160;  <span class="comment">// check if a valid candidate was available</span></div>
<div class="line"><a name="l00903"></a><span class="lineno">  903</span>&#160;  <span class="keywordflow">if</span> (!(best_index &lt; 0))</div>
<div class="line"><a name="l00904"></a><span class="lineno">  904</span>&#160;  {</div>
<div class="line"><a name="l00905"></a><span class="lineno">  905</span>&#160;    fitness_score_ = candidates [best_index][0].fitness_score;</div>
<div class="line"><a name="l00906"></a><span class="lineno">  906</span>&#160;    final_transformation_ = candidates [best_index][0].transformation;</div>
<div class="line"><a name="l00907"></a><span class="lineno">  907</span>&#160;    *correspondences_ = candidates [best_index][0].correspondences;</div>
<div class="line"><a name="l00908"></a><span class="lineno">  908</span>&#160; </div>
<div class="line"><a name="l00909"></a><span class="lineno">  909</span>&#160;    <span class="comment">// here we define convergence if resulting fitness_score is below 1-threshold</span></div>
<div class="line"><a name="l00910"></a><span class="lineno">  910</span>&#160;    converged_ = fitness_score_ &lt; score_threshold_;</div>
<div class="line"><a name="l00911"></a><span class="lineno">  911</span>&#160;  }</div>
<div class="line"><a name="l00912"></a><span class="lineno">  912</span>&#160;}</div>
<div class="line"><a name="l00913"></a><span class="lineno">  913</span>&#160; </div>
<div class="line"><a name="l00915"></a><span class="lineno">  915</span>&#160; </div>
<div class="line"><a name="l00916"></a><span class="lineno">  916</span>&#160;<span class="preprocessor">#endif </span><span class="comment">// PCL_REGISTRATION_IMPL_IA_4PCS_H_</span></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase</a></div><div class="ttdoc">PCL base class. Implements methods that are used by most PCL algorithms.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:69</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_af16a62638198313b9c093127c492c884"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">pcl::PointCloud::points</a></div><div class="ttdeci">std::vector&lt; PointT, Eigen::aligned_allocator&lt; PointT &gt; &gt; points</div><div class="ttdoc">The point data.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:410</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_plane_html"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_plane.html">pcl::SampleConsensusModelPlane</a></div><div class="ttdoc">SampleConsensusModelPlane defines a model for 3D plane segmentation. The model coefficients are defin...</div><div class="ttdef"><b>Definition:</b> sac_model_plane.h:137</div></div>
<div class="ttc" id="aclasspcl_1_1_stop_watch_html"><div class="ttname"><a href="classpcl_1_1_stop_watch.html">pcl::StopWatch</a></div><div class="ttdoc">Simple stopwatch.</div><div class="ttdef"><b>Definition:</b> time.h:66</div></div>
<div class="ttc" id="aclasspcl_1_1_stop_watch_html_a13f07f01df8ea1feb8d7d5fe3a0d22eb"><div class="ttname"><a href="classpcl_1_1_stop_watch.html#a13f07f01df8ea1feb8d7d5fe3a0d22eb">pcl::StopWatch::getTimeSeconds</a></div><div class="ttdeci">double getTimeSeconds()</div><div class="ttdoc">Retrieve the time in seconds spent since the last call to reset().</div><div class="ttdef"><b>Definition:</b> time.h:86</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_f_p_c_s_initial_alignment_html"><div class="ttname"><a href="classpcl_1_1registration_1_1_f_p_c_s_initial_alignment.html">pcl::registration::FPCSInitialAlignment</a></div><div class="ttdoc">FPCSInitialAlignment computes corresponding four point congruent sets as described in: &quot;4-points cong...</div><div class="ttdef"><b>Definition:</b> ia_fpcs.h:78</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_transformation_estimation3_point_html"><div class="ttname"><a href="classpcl_1_1registration_1_1_transformation_estimation3_point.html">pcl::registration::TransformationEstimation3Point</a></div><div class="ttdoc">TransformationEstimation3Points represents the class for transformation estimation based on:</div><div class="ttdef"><b>Definition:</b> transformation_estimation_3point.h:60</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a></div><div class="ttdoc">search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...</div><div class="ttdef"><b>Definition:</b> kdtree.h:63</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html_a457ebf1fc8f25e3b45d0bf9d55880f6f"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html#a457ebf1fc8f25e3b45d0bf9d55880f6f">pcl::search::KdTree::setInputCloud</a></div><div class="ttdeci">void setInputCloud(const PointCloudConstPtr &amp;cloud, const IndicesConstPtr &amp;indices=IndicesConstPtr())</div><div class="ttdoc">Provide a pointer to the input dataset.</div><div class="ttdef"><b>Definition:</b> kdtree.hpp:77</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html_a6be8fe286786c3b1aeda7d5369f9cb3e"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html#a6be8fe286786c3b1aeda7d5369f9cb3e">pcl::search::KdTree::nearestKSearch</a></div><div class="ttdeci">int nearestKSearch(const PointT &amp;point, int k, std::vector&lt; int &gt; &amp;k_indices, std::vector&lt; float &gt; &amp;k_sqr_distances) const</div><div class="ttdoc">Search for the k-nearest neighbors for the given query point.</div><div class="ttdef"><b>Definition:</b> kdtree.hpp:88</div></div>
<div class="ttc" id="acommon_2include_2pcl_2common_2distances_8h_html"><div class="ttname"><a href="common_2include_2pcl_2common_2distances_8h.html">distances.h</a></div></div>
<div class="ttc" id="acommon_2include_2pcl_2common_2distances_8h_html_a28ecc173df18d9175dee9f4dd042390b"><div class="ttname"><a href="common_2include_2pcl_2common_2distances_8h.html#a28ecc173df18d9175dee9f4dd042390b">pcl::squaredEuclideanDistance</a></div><div class="ttdeci">float squaredEuclideanDistance(const PointType1 &amp;p1, const PointType2 &amp;p2)</div><div class="ttdoc">Calculate the squared euclidean distance between the two given points.</div><div class="ttdef"><b>Definition:</b> distances.h:174</div></div>
<div class="ttc" id="acommon_2include_2pcl_2common_2distances_8h_html_a73e1d23717813eb053a0eb51411a4a23"><div class="ttname"><a href="common_2include_2pcl_2common_2distances_8h.html#a73e1d23717813eb053a0eb51411a4a23">pcl::euclideanDistance</a></div><div class="ttdeci">float euclideanDistance(const PointType1 &amp;p1, const PointType2 &amp;p2)</div><div class="ttdoc">Calculate the euclidean distance between the two given points.</div><div class="ttdef"><b>Definition:</b> distances.h:196</div></div>
<div class="ttc" id="acommon_2time_8h_html"><div class="ttname"><a href="common_2time_8h.html">time.h</a></div></div>
<div class="ttc" id="agroup__common_html_ga3166f09aafd659f69dc75e63f5e10f81"><div class="ttname"><a href="group__common.html#ga3166f09aafd659f69dc75e63f5e10f81">pcl::getMinMax3D</a></div><div class="ttdeci">void getMinMax3D(const pcl::PointCloud&lt; PointT &gt; &amp;cloud, PointT &amp;min_pt, PointT &amp;max_pt)</div><div class="ttdoc">Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud</div><div class="ttdef"><b>Definition:</b> common.hpp:228</div></div>
<div class="ttc" id="agroup__common_html_ga52d532f7f2b4d7bba78d13701d3a33d8"><div class="ttname"><a href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a></div><div class="ttdeci">void transformPointCloud(const pcl::PointCloud&lt; PointT &gt; &amp;cloud_in, pcl::PointCloud&lt; PointT &gt; &amp;cloud_out, const Eigen::Transform&lt; Scalar, 3, Eigen::Affine &gt; &amp;transform, bool copy_all_fields=true)</div><div class="ttdoc">Apply an affine transform defined by an Eigen Transform</div><div class="ttdef"><b>Definition:</b> transforms.hpp:42</div></div>
<div class="ttc" id="agroup__common_html_gaf5729fae15603888b49743b118025290"><div class="ttname"><a href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a></div><div class="ttdeci">unsigned int compute3DCentroid(ConstCloudIterator&lt; PointT &gt; &amp;cloud_iterator, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</div><div class="ttdoc">Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.</div><div class="ttdef"><b>Definition:</b> centroid.hpp:50</div></div>
<div class="ttc" id="astructpcl_1_1_correspondence_html"><div class="ttname"><a href="structpcl_1_1_correspondence.html">pcl::Correspondence</a></div><div class="ttdoc">Correspondence represents a match between two entities (e.g., points, descriptors,...</div><div class="ttdef"><b>Definition:</b> correspondence.h:59</div></div>
<div class="ttc" id="astructpcl_1_1_normal_html"><div class="ttname"><a href="structpcl_1_1_normal.html">pcl::Normal</a></div><div class="ttdoc">A point structure representing normal coordinates and the surface curvature estimate....</div><div class="ttdef"><b>Definition:</b> point_types.hpp:779</div></div>
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